The invention of microscopy by Antoni van Leeuwenhoek in 1674 has enabled the visualization of microscopic entities such as cells. The introduction of dyes that stained different components of cells by Paul Ehrlich some two hundred years later in combination with light microscopy can be considered as the first step in the new era of cell analysis. Improvements in cell labeling technology and instrumentation that can identify and differentiate the differentially labeled cells have significantly improved our ability to explore the world of cell biology. In the last 25 years automated blood cell counters have replaced manual examination of cytochemically stained blood smears. Criteria used for cell classification by morphometric means involved parameters such as nuclear to cytoplasmic ratio, cell and nuclear size and shape, the number and size of cytoplasmic granules. As cells gradually change their morphological appearance during maturation, it introduces more uncertainty in substantial inter-observer variations in the assignation of the cells. Morphological changes associated with malignancies can be associated with cellular appearance during maturational processes and abnormal frequencies of atypical cells are often used as criteria for assigning such cells as malignant.
Improvements in cell classification have come from identification based on immunophenotype. Early techniques such as formation of rosettes of sheep erythrocytes around T-lymphocytes have been replaced by flow cytometric analysis of cells labeled with fluorescent antibodies recognizing specific cell surface or intracellular antigens. Multi-parametric flow cytometry analysis has significantly improved the ability to enumerate and classify detected events on the basis of size and staining characteristics, but does not further discriminate detected events, for example, as cells by morphometric means. Present methods and devices using these principles are relied upon to diagnose and classify a variety of diseases such as leukemias and lymphomas, or to follow the progression of diseases such as AIDS. As technology improved, more information was obtained which in return lead to greater demands for expanding the sensitivity and specificity of detection methods for rare target species. An example of an application in need of further improvement is the identification and enumeration of circulating carcinoma cells of epithelial origin in the blood of cancer patients that may be present at frequencies of less than one carcinoma cell per ml of blood. Using a combination of epithelial cell enrichment by magnetic means in combination with analysis by multi-parametric flow cytometry, significant differences in the number of “circulating tumor cells” were found between healthy individuals and patients with breast cancer (Racila et al., Proc. Nat. Acad. Sci. 95, 4589-4594, 1998). In several studies, such “circulating tumor cells” (CTC) were defined as events expressing the following characteristics: positive for the epithelial cell marker cytokeratin, negative for the leukocyte marker CD45, positive staining with a nucleic acid dye, and light scattering properties that are compatible with cells. However, morphometric confirmations of the detected events as cells and further molecular evidence is lacking in flow cytometric methods, but is clearly needed to assure that the detected rare events are indeed tumor cells derived from a primary tumor. Automated image analysis systems have been introduced to reduce subjective errors in cell classification between different operators in manual methods, but such prior art systems without preliminary cell enrichment steps still inherently lack sensitivity. Several automated cell imaging systems have been described or are commercially available for cell analysis. The system developed by Chromavision, ACIS™ or Automated Cellular Imaging System (Douglass et al., U.S. Pat. No. 6,151,405) uses colorimetric pattern recognition by microscopic examination of prepared cells by size, shape, hue and staining intensity as observed by an automated computer controlled microscope and/or by visual examination by a health care professional. The system uses examination of cells on microscope slides and was designed for tissue sections. The SlideScan™ or MDS™ systems of Applied Imaging Corp. (Saunders et al., U.S. Pat. No. 5,432,054) is described as an automated, intelligent microscope and imaging system that detects cells or “objects” by color, intensity, size, pattern and shape followed by visual identification and classification. In contrast to the ACIS system this system has the ability to detect fluorescent labels which provides more capability. However, these and other currently available methodologies are not sufficiently sensitive for accurate classification and typing of rare events such as circulating tumor cells in blood. Accordingly, the present invention seeks to improve upon the aforementioned methodologies, and to provide simple and efficient means and methods for automated imaging of objects that can be used, for example, in conjunction with high sensitivity immunophenotyping, to permit detection, enumeration and accurate classification of rare target species, such as CTC in blood or other fluids.